Developing a micro-scale population exposure model: insights from the Italian context

Abstract

The increasing impacts of climate change and urbanization underscore the critical importance of micro-scale population data for enhancing natural risk management and emergency preparedness. Access to high resolution population information enables better correlation with the spatial variability of hazards, leading to more accurate damage estimations. However, such data are typically available at macro and meso-scales. In the case of Italy, for example, population data from the National Institute of Statistics (ISTAT) is provided at the census tract scale (meso-scale) for the entire country, despite the uneven distribution of residents within these areas. This study focuses on developing an exposure model for resident population in Italy at a finer spatial resolution than the currently available data. The model uses point data of resident population in the Emilia Romagna region, relating this information to residential building footprint area and volume, as well as land use features. The analysis reveals a notable portion of vacant residential buildings, with approximately 30% of Italian residential buildings reported as uninhabited by ISTAT. The study suggests that incorporating information on the type of residential buildings (main, secondary, or vacant) could significantly enhance the model's performance, especially in tourist-centric cities characterized by a high share of holiday houses. Additionally, the results of this study highlight the need for public entities to invest efforts in the development of a reliable and comprehensive spatial database that includes information on permanently inhabited properties.